测试科学与仪器2010，Vol.1Issue(1)：41-45,5.DOI:10.3969/j.issn. 1674-8042.2010.01.08
Vehicle Detection in Still Images by Using Boosted Local Feature Detector
Vehicle Detection in Still Images by Using Boosted Local Feature Detector
摘要
Abstract
Vehicle detection in still images is a comparatively difficult task.This paper presents a method for this task by using boosted local pattem detector constructed from two local features including Haar-like and oriented gradient features.The whole process is composed of three stages.In the first stage,local appearance features of vehicles and non-vehicle objects are extracted.Haar-like and oriented gradient features arc extracted separately in this stage as local features.In the second stage,Adaboost algorithm is used to select the mast discriminative features as weak detectors from the two local feature sets,and a strong local pattern detector is built by the weighted combination of these selected weak detectors.Finally,vehicle detection can be performed in still images by using the boosted strong local feature detector.Experiment results show that the local pattern detectur constructed in this way combines the advantages of Haar-like and oriented gradient features,and can achieve better detection results than the datector by using single Haar-like features.关键词
vehicle detection/still image/Adaboost/local featuresKey words
vehicle detection/still image/Adaboost/local features分类
天文与地球科学引用本文复制引用
Qing LIN,Young-joon HAN,Hern-soo HAHN..Vehicle Detection in Still Images by Using Boosted Local Feature Detector[J].测试科学与仪器,2010,1(1):41-45,5.基金项目
This work was supported by the Korea Research Foundation Grant funded by the Korean Government (MOEHRD),the MKE (The Ministry of Knowledge Economy,Korea),the ITRC (Information Technology Research Center) support program (NIPA-2009-(C109-0902-0007)) （MOEHRD）
